{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import chardet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('students.csv', encoding='gbk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.family']='SimHei'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(502, 11)\n",
      "性别           object\n",
      "年龄            int64\n",
      "学习压力          int64\n",
      "学习满意度         int64\n",
      "睡眠时间         object\n",
      "饮食习惯         object\n",
      "是否有过自杀的念头    object\n",
      "学习时间          int64\n",
      "经济压力          int64\n",
      "精神疾病家族史      object\n",
      "是否抑郁         object\n",
      "dtype: object\n",
      "性别           0\n",
      "年龄           0\n",
      "学习压力         0\n",
      "学习满意度        0\n",
      "睡眠时间         0\n",
      "饮食习惯         0\n",
      "是否有过自杀的念头    0\n",
      "学习时间         0\n",
      "经济压力         0\n",
      "精神疾病家族史      0\n",
      "是否抑郁         0\n",
      "dtype: int64\n",
      "               年龄        学习压力       学习满意度        学习时间        经济压力\n",
      "count  502.000000  502.000000  502.000000  502.000000  502.000000\n",
      "mean    26.241036    3.003984    3.075697    6.404382    2.928287\n",
      "std      4.896501    1.390007    1.373490    3.742434    1.425053\n",
      "min     18.000000    1.000000    1.000000    0.000000    1.000000\n",
      "25%     22.000000    2.000000    2.000000    3.000000    2.000000\n",
      "50%     26.500000    3.000000    3.000000    7.000000    3.000000\n",
      "75%     30.000000    4.000000    4.000000   10.000000    4.000000\n",
      "max     34.000000    5.000000    5.000000   12.000000    5.000000\n"
     ]
    }
   ],
   "source": [
    "print(data.shape)  # 数据形状\n",
    "print(data.dtypes)  # 列的数据类型\n",
    "print(data.isnull().sum())  # 缺失值检查\n",
    "print(data.describe())  # 数值型变量的描述性统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\30226\\AppData\\Local\\Temp\\ipykernel_7676\\741594157.py:2: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.countplot(data=data, x=\"性别\", palette=\"pastel\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "sns.countplot(data=data, x=\"性别\", palette=\"pastel\")\n",
    "plt.title(\"性别分布\", fontsize=14)\n",
    "plt.xlabel(\"性别\", fontsize=12)\n",
    "plt.ylabel(\"人数\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "sns.countplot(data=data, x=\"性别\", hue=\"是否抑郁\", palette=\"Set2\")\n",
    "plt.title(\"不同性别抑郁情况分布\", fontsize=14)\n",
    "plt.xlabel(\"性别\", fontsize=12)\n",
    "plt.ylabel(\"人数\", fontsize=12)\n",
    "plt.legend(title=\"是否抑郁\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AoGDCLAAAAABAwYRZAAAAAICCCbMAAAAAAAUTZgEAAAAACibMAgAAAAAUTJgFAAAAACiYMAsAAAAAUDBhFgAAAACgYMIsAAAAAEDBhFkAAAAAgIIJswAAAAAABRNmAQAAAAAKJswCAAAAABRMmAUAAAAAKJgwCwAAAABQMGEWAAAAAKBgwiwAAAAAQMGEWQAAAACAggmzAAAAAAAFE2YBAAAAAAomzAIAAAAAFEyYBQAAAAAomDALAAAAAFAwYRYAAAAAoGDCLAAAAABAwYRZAAAAAICCCbMAAAAAAAUTZgEAAAAACibMAgAAAAAUTJgFAAAAACiYMAsAAAAAUDBhFgAAAACgYMIsAAAAAEDBhFkAAAAAgIIJswAAAAAABRNmAQAAAAAKJswCAAAAABRMmAUAAAAAKJgwCwAAAABQMGEWAAAAAKBgwiwAAAAAQMGEWQAAAACAggmzAAAAAAAFE2YBAAAAAAomzAIAAAAAFEyYBQAAAAAomDALAAAAAFAwYRYAAAAAoGDCLAAAAABAwYRZAAAAAICCCbMAAAAAAAUTZgEAAAAACibMAgAAAAAUTJgFAAAAACiYMAsAAAAAUDBhFgAAAACgYMIsAAAAAEDBhFkAAAAAgIIJswAAAAAABRNmAQAAAAAKJswCAAAAABRMmAUAAAAAKJgwCwAAAABQMGEWAAAAAKBgwiwAAAAAQMGEWQAAAACAgq3SYXb8+PHp1atX1lhjjQwcODANDQ3lHgkAAAAA4CNbZcNsfX19dt9992y++eYZPXp0JkyYkOHDh5d7LAAAAACAj2yVDbN33313ZsyYkQsuuCA9evTI4MGDM2zYsHKPBQAAAADwkVWVe4DmjBs3Lr17907r1q2TJD179syECROaPb++vj719fWlxzNmzEiS1NXVrdxB38eshQvL+v6sOhbUzy73CKxCyv2zaVXhZyRL8nOSxfyMfJefkSzJz0iW5Ofku/ycZDE/I1lSuX9GLn7/5dmStaJhFd249Sc/+Unmzp2byy67rHSsc+fOefbZZ7PGGmssdf5pp52WX/7yl0WOCAAAAACwlMmTJ6dr167LPGeVXTFbVVWVmpqaRsdqa2sze/bsJsPsoEGDcvzxx5ceL1q0KG+99VY6duyYioqKlT4vLEtdXV26deuWyZMnZ/XVVy/3OACrHD8nAZrnZyRA8/yMZFXT0NCQmTNnZu21137fc1fZMNuhQ4eMHz++0bGZM2emZcuWTZ5fU1OzVMht3779yhoPPpTVV1/d/1AALIOfkwDN8zMSoHl+RrIqadeu3XKdt8re/KtXr14ZNWpU6fGkSZNSX1+fDh06lHEqAAAAAICPbpUNs9tuu23q6upy7bXXJkkGDx6cHXbYIZWVlWWeDAAAAADgo1lltzKoqqrK0KFDs99++2XgwIFp0aJFHnzwwXKPBR9KTU1NTj311KW22wDgXX5OAjTPz0iA5vkZycdZRUNDQ0O5h1iW1157LWPGjEnv3r3TsWPHco8DAAAAAPCRrfJhFgAAAADgk2aV3WMWAAAAAOCTSpgFAAAAACiYMMunyvDhw1NRUbHUx/Dhw9/3tWeccUbWWmuttGnTJv3798+0adOW6/223377jz44QEGOOeaYRj8f119//Q/0+p/97GfZfffdl+vcBx98MOuuu+6HmBLgXaeddloqKirypz/9KUly+eWXL/ff7YpUjr8T+rsrMHz48Gy22WblHuN9bb/99oX+3H7zzTeXagLXX3/9+76u6Dn5dBBm+VTZf//98/bbb5c+Jk+enE6dOmWbbbZZ5utGjhyZm266KSNHjszYsWOzcOHCHH/88QVNDVCc0aNH56677ir9nHziiSeW+7X/+c9/cvnll+fiiy9eiRMCLG3ChAlJkqeeeqrMkyTrrrtuHnzwwbLO4O+uwKpoVfmX8mPGjMk222zTqA3ss88+5R6LT6mqcg8ARWrZsmVatmxZenz55Zdnzz33TI8ePZb5uscffzy77rprNtxwwyTvBt7LLrtspc4KULQFCxbkqaeeyrbbbps2bdp8oNcuWrQoRxxxRP7v//4v66233kqaEGBplZWVpSA7fvz4VFZWlnmi8vN3V4Dm/etf/8rXvva1tG/fvtyjgBWzfHrNnTs3F198cU466aT3PXeTTTbJH/7whzz//PN54403MmzYsOy4447L/V5XX3111lprray11lq5/fbbS8dHjhyZzTbbLGussUb233//TJ8+PcnSv0b2wgsvpKKiovR48a9QXHDBBVlnnXXyl7/8pfTc73//+3Tv3j2rrbZadtppp+X6tTWAJHnyySezaNGibLbZZmnVqlV23nnnvPTSS8v12iuvvDJPPvlk1l133dx5552ZN2/ecr/vnXfemXXWWScdOnTIr3/969Lx8ePH5+tf/3ratWuXXXfdNVOmTEnS9GqLioqKvPDCC0mSgw8+OKeddlquv/76bLjhhrniiitK5913333ZeOON07p162y99dZ57rnnlntOYNW0xRZblMLs008/nf+vvXuPrunM/zj+PrnKRQS5IAmJUNVOQlHaiGKoS6MYXYqhJFN1aV061SoWFaNotIairmtcSgmDJe6C6ZiKa427qRHiELdEE5GIkMv5/ZGVXWfkcuiMX/B5rbUXZz/7efZzzlrne55897Of3bhxY6OspDgCpceKQ4cO0axZMypVqkS3bt3IyMgosx8dOnTAZDJhNptp3bo1JpOJL774wuqYksaEcXFx1KtXDzc3N9q0acOVK1eAX8aEJdUricauImKLbdu2ERISgqenJ/379+fu3btG2fTp06lRowYVK1akR48e5OTkAGCxWBg5ciTe3t5UrlyZIUOGYLFYSj3PtWvXMJlMtG7dGrPZbCwfcO3aNeOY27dv0717d9zc3AgLC+P69esA5OfnM2TIEKpUqYK3tzfjxo0z6rRq1Ypvvvmm2HqlOXjwIOvWrcPd3Z2AgABmzZpl82dWWj8/++wzqlevTmBgIHPmzLHq5/1LIERHRxMZGQn8Ei9TU1N5++23rSY43Lt3j8jISCpXroyPjw+TJ0+2uZ/y5FBiVp5ZK1asoFmzZsYf940aNcLT0/OBbcOGDXTs2JHg4GCCg4Px9fUlKyuLUaNG2XSekydPsm7dOhISEoiKiuLDDz8E4NKlS7zxxht88MEHHD58mKysLCM422L+/Pns2LGD+fPn06xZMwAyMzPp168fU6ZM4dSpUzg4ODBt2rSH+VhE5Bl2+vRp6tWrx7Jlyzh+/DgODg4MGDAAgK5duxYbI2fPnk1WVhbjx4+ndu3amM1mpk+fTnh4OHfu3CnznD///DMxMTFs2bKFP/3pT4wYMYKcnByysrJo164dr7/+OsePHycgIIAuXbpQUFBg03vZvn07s2fP5quvvqJz587G/j59+hAVFcWZM2d44YUXrAb3IvJkqlu3LhcuXODKlSt4enri4uICYFMcKS5W3Lx5k44dO9KxY0eOHz/OrVu3GDFiRJn9WLt2Lenp6QQEBLBx40bS09P54x//aJSXNCYsuoV29OjRJCYm4uPjw+eff15mvdJo7CoiZUlMTKRLly4MHz6cQ4cOcfDgQb788kug8CLXJ598QmxsLP/85z9JTExk6dKlQGHcXLhwITt37uQf//gHcXFxxMfHl3ouX19f0tPT2bhxIwEBAcbyAb6+vsYxEydOpEWLFhw7doyMjAxjlv/8+fPZsGED+/fvZ9euXcydO5eDBw+WWa+s9x4ZGcnp06f585//zMiRI9m/f79Nn1tJ55sxYwYrV65k8+bNLFmyhOjoaNavX29TmwDdunWjYcOGLFu2zNi3aNEiEhISOHjwIHFxcUyaNImffvrJ5jblyaClDOSZNW/ePKKjo43XGzduJDc394HjfHx8WLNmDRcvXuT06dN4eXkxcuRI+vTpw9q1a8s8z+3bt1m6dCk+Pj784Q9/ICYmBoDly5cTFhbGe++9B8DcuXPx9/e3umpYmqysLHbv3m21NIODgwMODg7cu3eP6tWrs2HDBpuTGCIivXv3pnfv3sbrOXPmEBQUxK1bt5g/f36xidYqVaqwbt06bt++zffff4+Xlxd5eXmEhISwbNkyI7FbkqysLObOncuLL75I3bp1GTp0KNevX2fv3r1UrFiR8ePHA/D111/j7e1tNRAvzblz5zh79iyVKlWy2u/i4kJubi5VqlRhwYIF5OXl2dSeiJRf9vb2BAUFsXHjRkJDQ0lNTQUKx3YlxZFXXnkFKD5WbN68GUdHR8aPH4/JZOLjjz+mb9++ZfbDzc0NADs7O9zd3R+4RbakMaG7uztms5lKlSrx448/cvv2bVJSUsqsVxqNXUWkLKtWraJhw4b0798fgPfff59FixYxduxYnJ2dgcIZm0FBQRw4cMCoV3TxKzc3l0aNGnH+/Hns7Eqf82cymfD09MTd3R07O7tilxAICwtj2LBhAHTp0oVLly4BhRfV+/TpQ3Z2NseOHcPe3p4zZ87QtGnTUuuV5v71yGvWrMnWrVtZs2aN8dtQmpLOt2DBAiZMmECjRo0AGD58OPPmzaNr165ltgnwxhtvMHr0aKt9Li4uWCwW8vLyePXVV0lPT8fBQWm8p41mzMozKTExkcTERKtbuvz8/AgMDHxgc3V15bvvvmPw4MHUr18fb29vZsyYwbp164zbt0pTv359fHx8AKwGopcuXbK6TcHPzw9nZ+dibxvOzs5+YN+gQYOs2oPCwB0bG8uCBQvw8fGhc+fONv0wiYgUx8fHh4KCAq5evYqvr2+xMdLDw4Pk5GReeeUVvLy8gMI/tENDQ21aJqBy5cqEhoYCv8RIi8XCpUuXCAoKMo6rUKECfn5+NsfIfv36PZCUhcLEwvfff4+fnx+tW7fm5MmTtn0YIlKuhYaGsnr1aiOeADbFkeJiRXJyMqmpqVSuXBlPT0/efvttUlNTjdt4H1VJY0KLxcKoUaPw8/Nj1KhR5Obmkp+fX2a90mjsKiJlSU5O5siRI8ZdUB9//LHxfQ4KCmL+/PmMHj0ab29v3nnnHdLT0wFo2bIlI0eOJCoqCh8fH4YNG2a1BMKjun85FCcnJ2N5hKSkJFq3bk3jxo2JjY3Fzc3NKkaWVO9h+Pj4cPny5V/Vz/+MkcHBwSUuCVZcjCxK9t6vV69edOvWjc6dO1OjRg3jQqM8XZSYlWfS6tWr6dSpE46OjjYdX1BQYDVzoWhmwP0/CCXx8PAodn/NmjU5f/688frKlSvcvXuXWrVqYTKZrGYLHD58+IH6RbMy7peWloavry979uzh+vXreHl52XS7m4gIwCeffMKKFSuM1/v27cPOzo6AgIBS6/n7+z8wm9ZsNuPn51fmOUuLkUlJScbru3fvcuXKlV8VI7Ozs8nLy2PHjh3cuHGD8PDwh7oNV0TKr9DQUP72t79ZJWZLiyNFiosV/v7+NG7cmKNHj3L06FGOHTvGkSNHbB432tnZFZsYKCnerVixgv3792M2m9mzZw9vvvmmTfVKo7GriJTF39+fN9980yrW7dixAyj8fjdp0oRDhw5x4cIFbty4wcSJEwE4f/483bp148SJE5w8eZKEhATmzZtn0zlLio9QcuwZPnw4HTt25PLly6xdu9aYCFBWvZKYzWaaN29u1Y99+/ZZ/TaUxtYYef78eaPNR42RiYmJfPDBB5w9e5YffviBJUuWPNTyCPJkUGJWnknbtm2zutJVlhYtWrBgwQLmzZvH0qVL6dmzJ2FhYVStWvWR+9C7d2/27t3LwoULSUpKYvDgwXTt2hVfX1/8/Pw4ffo0t27dIjU1lalTp9rUZkpKCq1atWLbtm2kpaUB6DZdEbFZgwYNGDt2LLt27SI+Pp5BgwbRt29fXF1dS60XERHB6dOnmTdvHsnJycycOZNjx47RrVu3R+5Lp06dyMzMZMKECZjNZoYNG0bdunV5+eWX8fPz4+rVq5jNZrKzs22ePZCXl0f79u357rvvSElJMW4NE5EnX1FC9v7EbGlxpDQRERFcvHiRgwcP4uLiwpo1a+jQoYPNs7CCg4OJj4/n6tWr7Nq1q8zjMzMzsVgspKWlsXXrViZOnPhIM77up7GriBTJzc0lOTnZasvNzaVnz5788MMPnD17FmdnZ2bNmkVUVBRQuNZ0u3btSEhIIDMzE/jlu7lz505+97vfceTIEePCvK3f29q1a3PlyhWOHDlCYmIiR44cKbNOZmam8R4+++wzDh069KtiZM2aNUlJSWHMmDEcPnyYMWPGsH//ft59991HbhPgvffeIzo6miNHjrB7925mzJjBoEGDgMI7DPbt2wfA+vXrSUhIsKnN5cuXG2vhFs1KVox8+igxK8+cO3fucODAAcLCwmyuM3ToUHr27MnEiRMZMGAAlSpVYvny5b+qHwEBAWzevJlvvvmGl156CVdXVxYvXgzAb3/7W9q1a0dISAgRERGMGTPGpjaff/55pk2bxuDBgwkODubMmTPGAu4iImXp06cPPXr04K233qJXr1506NCB2bNnl1mvatWqbNmyhaVLl/Lcc8/x9ddfs3r16jJn2pbG3d2d7du3Ex8fT0hICBcvXiQuLg47Ozvq1KnD8OHDad68OeHh4QwfPtymNj08PFi+fDmff/45wcHBbNy40eYZHiJSvjVo0AAPDw/joa5QehwpTdHDX6dNm0bt2rX561//yoYNG2xe1+/LL79k8+bN1KxZ0+p5BiXp168fgYGB1K9fnwkTJjBw4ED+9a9//aqlEzR2FZEip0+fJiAgwGo7duwYwcHBfPvtt3z00UfUqVOH48ePs3LlSgDatWvHwIED6d69O8899xwWi4WxY8cCEBUVRcuWLWnfvj2hoaHUrVuX999/36a++Pv7M2XKFNq2bUuDBg3Yu3dvmXViYmJYs2YNoaGhXLt2jddff92mhG5JTCYTa9euZceOHYSFhbFt2zbi4+OpW7fuI7cJ8OGHH9KzZ086duxI3759iY6OpkuXLgCMHj2ahIQE6tevz8qVKxkyZIhNbX766af4+PjQvHlzwsLC6Ny586+a+CDlk8nyay/HioiIiIiIiIiIiMhD0YxZERERERERERERkcdMiVkRERERERERERGRx0yJWREREREREREREZHHTIlZERERERERERERkcdMiVkRERERERERERGRx0yJWRERERGR/6Hc3Nz/7y6IiIiISDnk8P/dARERERGR/waLxYLJZCqxfM6cOVy8eLHE8iFDhuDv7//Q57169SqvvvoqS5cupWXLllZl165do2nTpsycOZOuXbuSn59PTk4Ojo6OODo6ltpfEREREXm6KTErIiIiIk+EQ4cOcfbsWXJzc7l9+zZpaWmkpqZy6dIlTp06xUsvvURsbCwxMTGMGjXKqu6qVatYvXo1eXl5hIeHW5VZLBamTp1Kjx49jMTszZs3uXnzptVxTk5O1KhR44F+2dnZYTabyc/Pf6CsWrVqREREEBUVRcOGDUlOTqZFixYlvsdKlSo9cF4REREReTopMSsiIiIi5Y6vry8pKSnG6xUrVuDh4cHy5cupUKECrq6ubN++nbZt2xIREUFkZCTVq1fHYrHg5uZG8+bN2bRpEwChoaG4ublhb29Pq1atiI6OtjpXXl4eU6dOxcnJydg3c+ZMxo8fb3VcgwYNOHr06AN9dXBwsPq3SGZmJvn5+UybNo20tDTMZjNNmzYlMTERZ2dnnJ2drWbMLl26lJiYmEf6vERERETkyaPErIiIiIiUO46OjixevJjIyEgCAwNxcnIiIiKCiIgI45gmTZrQvn17IiMjreq6urri4OCAp6cnUDij1dXVtcxlA+4vd3BwIDg4mMTERABGjRrFzp07uXDhAtevX8fR0REHBwfs7Oy4desWAOfPn8fZ2Zk6depQtWpVhg0bxsmTJzl06BCrVq0y2g4ODi72/G5ublbJYRERERF5uikxKyIiIiLljqOjI7m5ueTk5GCxWMjPz6dKlSrY29vj5ORExYoVMZvNjB49mkmTJpGamoqbmxuDBg0iKCio2PYAjh8/zvLly63KCgoKALh3794Dx9/PwcGBhQsXMn36dBwdHbGzs8PO7pdn6Q4bNoy8vDxiY2Pp3LkzHh4euLi4GOcoSuD+J1dXVyVkRURERJ5BdmUfIiIiIiLyeNnb2zNgwABcXFy4ePEirq6upKWlERERQa9evfjpp5948cUXmTJlCjt27CAjI4MzZ84wbtw4ABISEvDy8sLLy4tLly4Z7V68eJE9e/awZ88e+vbtS1xcHHv37mXgwIHGDFvAKuF6/75JkyaRnZ1NRkYG6enp/Pzzz5w7dw6ALVu2kJ2dTefOnQGM5C0UPgSscuXKxW5/+ctf/lcfo4iIiIiUY5oxKyIiIiLl0oIFC3jnnXeoV6/eQ9dt3rw5f//73wEIDAw09nfq1MlYY3b16tUMHTqU11577YH6JpOJc+fOWS1vEBYWBhTOfr1w4QK1a9e2uT9FM2dPnDjBb37zG2N/nTp1qFChgs3tiIiIiMjTQzNmRURERKRccnR0pEKFCphMJn788Udefvlltm7dSmxsLOHh4Zw5c4bJkyfTvXt3AFq3bs3AgQNtbt/Ly4sbN24AhcnW7Oxso8zOzo5atWqRlJREUlISgwYNMpK0o0ePpk2bNuTl5dl8rqK6mZmZ3Lx509gKCgrKXPtWRERERJ5OSsyKiIiISLkUFRWFyWTCbDbz/PPP8+233xIeHk6HDh1YsmQJgYGB9O/fn6+++gqAefPmMXLkSAB2796NyWQy6heZMGGCsf/s2bO89dZbmEwm7O3tjRmxUJiodXBwIDAwkMDAQCpVqmSUDRw4kMuXL7Ns2bKHfk9hYWFWyxgkJSU96scjIiIiIk84JWZFREREpFxavHgxFouFWrVq4e7uTv369alYsSKenp7UqVMHZ2dnfHx8qFWrFgD16tUjODgYKFzKID09nfT0dAICAow2P/30U2N///796d+/P+np6dy4cYO4uDjjuPz8/Af6Y7FYAKhduzYRERFMmTLFeHCYrU6cOIHFYjG2ov6KiIiIyLNHa8yKiIiIyFPHwcHBeJjX/Q/yqlChgrE/LCyMuXPnGq+rVq1qHFdQUEBeXh4XLlwAICMjwyoJO2LECO7cuVPsQ8KKU5TUfdgyEREREXl6KTErIiIiIuXe5cuXqVy5Mnfv3sXe3p7Y2FhSUlL46KOPcHZ2BqBu3bq0a9eOli1bkpOTYyRV8/Lyil0Ptn379vTv35/k5GT8/f2tyvLz8zGbzQQFBRn7mjRpYvw/PDz8ofqfk5MDQEhISIllIiIiIvJsUWJWRERERMqdgoICoqKiiIqKAqBixYrMnDnTeBgYFC5L0LFjR1q1amXU8fX15cSJExw4cMAqqZqdnW3MeD1//jzvvvsumzZton379syZM4fJkydz69YtPDw8gMLEbHBwMImJiQCMGzeO+Pj4h3oP+fn5xmxYX19f0tPTiz3O1dUV0MxZERERkWeN1pgVERERkXInPz/fao1ZJycnunTpQqtWrWjbti1t27bFw8ODF154gbZt29KmTRtatGhBixYtyM7OpmXLlsY6rkOHDsXb25vLly8TFxdHSEgIzs7O5OTk8NlnnzFr1iz+/e9/ExYWxpo1awBwd3enevXqRn8mTpzIgQMHiu1rWloagJEwLpKVlcW9e/eAwuUUPD09i90yMjLYtGkT69atw8XF5X/xcYqIiIhIOWSy6NK8iIiIiJQz1apV44svviAyMpIZM2bQpk0b1q1bx+TJk3F2dn5gbVeLxcLdu3e5fPkydnZ2ZGdn4+fnZ5Snp6dTrVo13N3dmT17Nr169TLKoqOjiYmJwcnJiVOnTj2wrEFJbt26RevWrUlMTCQ/P5+kpCS8vb2N8t///vecOXOGw4cPl9mOt7c3Li4uTJgwgeHDh9t0fhERERF5sikxKyIiIiLlTkpKChUrVvyvziBdv349TZs2pUaNGg+ULVq0iDp16vDaa689VJurV68mMzOTdu3aERAQ8Mh9O3v2LMHBwTY/TExEREREnnxKzIqIiIiIiIiIiIg8ZrokLyIiIiIiIiIiIvKYKTErIiIiIiIiIiIi8pgpMSsiIiIiIiIiIiLymCkxKyIiIiIiIiIiIvKYKTErIiIiIiIiIiIi8pgpMSsiIiIiIiIiIiLymCkxKyIiIiIiIiIiIvKYKTErIiIiIiIiIiIi8pgpMSsiIiIiIiIiIiLymP0foZvK6Aw6u3sAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1700x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(17, 10))\n",
    "sns.countplot(data=data, x=\"睡眠时间\", hue=\"是否抑郁\", palette=\"Set1\")\n",
    "plt.title(\"不同睡眠时长与抑郁情况的关系\", fontsize=14)\n",
    "plt.xlabel(\"睡眠时间\", fontsize=12)\n",
    "plt.ylabel(\"人数\", fontsize=12)\n",
    "plt.legend(title=\"是否抑郁\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\30226\\AppData\\Local\\Temp\\ipykernel_7676\\1410191558.py:2: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.boxplot(data=data, x=\"是否抑郁\", y=\"学习压力\", palette=\"coolwarm\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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WjTfeqF9//VU//fQTZ5wAAAAAXDEqdMOI+Ph4vfXWW9q1a5duuOGGinxpAAAAAPCqC9qqfOfOnQoNDZWfn58OHTokSfrll1/Url07SVJaWpokuZ8DAAAAgMvdBcVT586dZbfb3fddLpeaNGlSbJ3L5eLSPQAAAABXhAuKpzVr1iggIEAWi0W//PKL+vTpo5SUlGIbQ+zfv1933HFHRcwJAAAAAF51QfHUtm1b96+DgoIkSddcc02xzSQCAsxfPisrS3v37lXz5s1VvXr1CxkLAAAAACrNRW8YkZeXJ0nn9eG55/roo4/UqFEjJSYmKiYmRh999FG5x6xdu1ZXXXWVoqKiNH369Av+2gAAAABgokLiKTw8XLm5ucWeKwoql8tV6vEnTpzQqFGjtG7dOu3YsUPJycl6/PHHy/yaGRkZSkhI0IABA7Rp0yYtXrxYa9asubhvBAAAAADKcN6X7Z27AUSbNm10/PjxEtfm5ubK5XIpLy9PNputxDV2u12vvfaa4uPjJUnXXXedMjMzy5xh8eLFqlevniZOnCiLxaJJkyZp3rx56tq1a4nrHQ6HHA6Hx9f0ZVlZWTp16pS3x8AVLiMjw+N/gcoUEhKiyMhIb49xWTqW4yh/EQBcBq6E38/OK55cLpf7PU7nCgwMVHh4uOrUqaP4+HjdcMMNuuOOO8q9nC82NlaDBg2SJDmdTs2YMUN9+/Yt85jt27era9eu7pDr2LGjnnzyyVLXT506VZMnTy7zNX1FVlaWps+YoXyn09ujoIpYsmSJt0dAFRBgtWrc2LEE1HkICQmR1RqgT3eleXsUAKgwVmuAQkJCvD3GBTOOp5o1a2ru3LkKCwtTcHBwsTNQhYWFyszM1K+//qpt27bpqaee0ujRo/W73/1O48aNU8+ePct8/e3bt+t3v/udAgMDtXv37jLX2u12tWrVyn0/PDxc6enppa5PSkrSuHHjPI6PjY0t82t4y6lTp5TvdKp5+wQFh0V5exwAuGg52Uf1n28/1qlTp4in8xAZGamxY8dxJQIqXUZGhpYsWaJ7771X0dHR3h4HV7jL/UoE43gKDQ3VAw88YPzCubm5ev/99zVp0iSlpKSUG0/x8fFasWKFxo4dq8TERC1durT0oQMCPC4DDAoKUk5OTqnrbTZbqZcN+qrgsCiFRtbx9hgAAC+KjIy8rP+SgctLdHS06tev7+0xAJ92QVuVmwgKCtKwYcPUv3//Yp//VBKLxaJ27dpp4cKFatKkibKyskr9A6NGjRoe79PIzs5WYGBgRY0OAAAAAMVc9G575alWrVqZYbN27VqP3fUCAwNlsViKfWbU2Tp06KBNmza576ekpPAvJQAAAAAqVaXHU3maN2+uOXPmaM6cOUpLS9NTTz2l7t27Kzw8XHa7Xc4SNk5ISEjQxo0btWrVKjmdTr388svq0aOHF6YHAAAAUFWc12V79evXV3R0tMLDwxUcHCybzaagoCD3e4qKfh0UFKSQkBC1bdtWvXr1KvM169atq6VLl+qxxx7ThAkT1KNHDy1atEjSmfdBvfbaa7rjjjs8jomKitKMGTPUu3dvhYaGKjIyUgsWLDivbxwAAAAAzsd5xdPhw4f1xz/+UQEBAXI4HMrLy1NeXp5OnjypY8eOue87HA6lpaXp8OHDevLJJ/X888+X+bp/+MMftGvXrmKPp6amlnrMiBEj1KNHD+3Zs0edO3dWaGjo+XwrAAAAAHBeznvDiOeee061atUqd53L5VJCQoKWLVtWbjxdqLi4OMXFxVXKawMAAADA2SrsPU9JSUlavHix+77FYtGNN96offv2VdSXAAAAAACvqbB4CgwM1KRJkzweKywsVOfOnZWfn19RXwYAAAAAvOKi4iknJ0dbt26VJI0aNUrp6en6/PPP3c+PGTNGK1asUEBApX2cFAAAAABcEhcVT2PGjNGtt96q9PR01a5dW/fcc49mz57tfp5NHAAAAABcKS44nlatWqV58+bpueeeU7169SRJiYmJ+uyzz3ifEwAAAIArznnHU0FBgRwOh0aOHKnf//73Gj9+vPu5W265RU2aNNFLL71UoUMCAAAAgLcZx1NhYaEsFoucTqfef/99paena+7cucXWDR48WO+++64OHz5coYMCAAAAgDcZx1NeXp5cLpfy8/M1dOhQbdy4UY0aNSq2rn///nI4HJo2bVpFzgkAAAAAXmUcT/7+/nr99dcVFRUlSWrbtm2J65o2barExEQNHTq0IuYDAAAAAJ9gvIe41WrVww8/bLR2zpw5FzwQAAAAAPiiCvuQXAAAAAC4kl1QPOXn5+v777/Xzp07tWvXLo/nMjMz9e6771bIcAAAAADgKy4onjIzM9W+fXu1adNGAwYM8HguPT1dI0aMqJDhAAAAAMBXGL/n6e9//7tCQ0OVkJDgfmz37t0KCwvzWBcYGKjAwMCKmxAAAAAAfIDxmacpU6bozjvv1IQJE5STkyOLxaJGjRopPDxc999/v9asWeNea7FYKmVYAAAAAPAW43javHmzXn75Zb3//vu66aab3I/n5uZqwYIF+stf/lIZ8wEAAACATzCOp/DwcI0bN04//fST7r///mLPb9y4UR9++GGFDgcAAAAAvuK8N4zIy8vTo48+WuzxxMREjR07Vt98843y8/O1fv16rVu3Tl9//bVOnTpVIcMCAAAAgLcYx1NOTo6GDh2q1q1b69ixY3K5XO7nLBaLpk6dKqfTqWHDhunkyZPq0qWLbr31VnXu3Fk9e/aslOEBAAAA4FIxjqeHHnpIH330kcaOHavQ0NBim0JUr15dO3fu1IYNGxQZGans7GxlZ2dr5syZ2rRpk06fPl3hwwMAAADApWIcT5MnT9bWrVs1bty4Urcir127tmrWrClJCgkJUUhIiFq2bKmAgAAdPXq0YiYGAAAAAC8w/pynJk2aSDpz+d7ZnE6nJKmwsFB+fsVbrFWrVvrll19Uq1ati5kTAAAAALzqvDaM2LBhg5o0aaKVK1e6H3M4HHK5XKVelle3bl3CCQAAAMBlzziedu/erd69e+uaa65RmzZtJJ3ZKKJevXraunWrgoODK21IAAAAAPA243hq1qyZxowZo08//VS1atWSy+XSfffdp3Hjxqldu3buDSQKCgqUn59faQMDAAAAgDcYv+cpICBAU6ZMkSQFBQXpzjvvlJ+fn3Jzc4utLXp/FAAAAABcKYzj6WwRERFaunRpic+1atVKKSkpFzUUAAAAAPia89owAgAAAACqKuIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwIBPxNOyZcvUuHFjBQQEqG3bttq9e3e5xyQkJMhisbhv3bp1uwSTAgAAAKiqvB5P+/bt07Bhw/Tiiy/q0KFDat68uRITE8s97ttvv9WOHTt0/PhxHT9+XMuWLbsE0wIAAACoqgK8PcDu3bv14osv6t5775UkjRw5UrfddluZxxw6dEgul0vXXHPNpRgRAAAAALwfT3369PG4v3fvXjVr1qzMY7Zs2aKCggLFxMTo+PHj+uMf/6g33nhD1atXL3G9w+GQw+Fw37fb7Rc/OAAAAIAqxeuX7Z0tLy9Pr776qkaMGFHmuj179qhNmzZavny5vvnmGx04cEBJSUmlrp86daoiIiLct9jY2IoeHQAAAMAVzqfi6dlnn1VISEi573lKSkrSypUr1aZNG7Vu3VrTpk3T0qVLy1x/4sQJ9y0tLa2iRwcAAABwhfP6ZXtFvvzySyUnJ+ubb76R1Wo9r2Nr1aqlzMxMORwO2Wy2Ys/bbLYSHwcAAAAAUz5x5unAgQMaMGCAkpOT1apVq3LX9+vXTxs2bHDf37Rpk2rXrk0gAQAAAKg0Xj/zdPr0afXp00e33367+vbtq5MnT0qSQkJClJ2drWrVqhU7E9W6dWuNHTtWM2bM0NGjR5WUlKSRI0d6Y3wAAAAAVYTXzzytWLFCP/74o+bOnauwsDD37eDBg4qPj9fy5cuLHfPEE08oPj5ePXv21MiRIzVq1Cg9/fTTXpgeAAAAQFXh9TNPt99+u1wuV4nPpaamlvi41WrVvHnzNG/evEqcDAAAAAD+x+tnngAAAADgckA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYMAn4mnZsmVq3LixAgIC1LZtW+3evbvcY9auXaurrrpKUVFRmj59+iWYEgAAAEBV5vV42rdvn4YNG6YXX3xRhw4dUvPmzZWYmFjmMRkZGUpISNCAAQO0adMmLV68WGvWrLlEEwMAAACoigK8PcDu3bv14osv6t5775UkjRw5UrfddluZxyxevFj16tXTxIkTZbFYNGnSJM2bN09du3Ytcb3D4ZDD4XDft9vtFfcNVJKc7KPeHgEAKgS/nwEArhRej6c+ffp43N+7d6+aNWtW5jHbt29X165dZbFYJEkdO3bUk08+Wer6qVOnavLkyRc/7CX0n28/9vYIAAAAAM7i9Xg6W15enl599VWNGzeuzHV2u12tWrVy3w8PD1d6enqp65OSkjxe0263KzY29uIHrkTN2ycoOCzK22MAwEXLyT7KPwgBAK4IPhVPzz77rEJCQsp9z1NAQIBsNpv7flBQkHJyckpdb7PZPNZfDoLDohQaWcfbYwAAAAD4/3wmnr788kslJyfrm2++kdVqLXNtjRo1lJGR4b6fnZ2twMDAyh4RAAAAQBXm9d32JOnAgQMaMGCAkpOTPS7HK02HDh20adMm9/2UlBTVr1+/MkcEAAAAUMV5PZ5Onz6tPn366Pbbb1ffvn118uRJnTx5Ui6XS3a7XU6ns9gxCQkJ2rhxo1atWiWn06mXX35ZPXr08ML0AAAAAKoKr8fTihUr9OOPP2ru3LkKCwtz3w4ePKj4+HgtX7682DFRUVGaMWOGevfurdq1a2vv3r165plnvDA9AAAAgKrC6+95uv322+VyuUp8LjU1tdTjRowYoR49emjPnj3q3LmzQkNDK2lCAAAAAPCBeLoYcXFxiouL8/YYAAAAAKoAr1+2BwAAAACXA+IJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIABn4mno0ePKi4uTqmpqUbrExISZLFY3Ldu3bpV7oAAAAAAqrQAbw8gnQmnPn36GIeTJH377bfasWOHYmJiJElWq7WSpgMAAAAAHznz1L9/fw0cONB4/aFDh+RyuXTNNdcoMjJSkZGRCgkJqcQJAQAAAFR1PhFPc+fO1ejRo43Xb9myRQUFBYqJiVFISIj69++v48ePl7re4XDIbrd73AAAAADgfPhEPMXFxZ3X+j179qhNmzZavny5vvnmGx04cEBJSUmlrp86daoiIiLct9jY2IsdGQAAAEAV4xPxdL6SkpK0cuVKtWnTRq1bt9a0adO0dOnSMtefOHHCfUtLS7uE0wIAAAC4EvjEhhEXq1atWsrMzJTD4ZDNZiv2vM1mK/FxAAAAADB1WZ556tevnzZs2OC+v2nTJtWuXZtAAgAAAFBpfDqe7Ha7nE5nscdbt26tsWPHasOGDfrXv/6lpKQkjRw50gsTAgAAAKgqfDqe4uPjtXz58mKPP/HEE4qPj1fPnj01cuRIjRo1Sk8//bQXJgQAAABQVfjUe55cLpfH/dI+NNdqtWrevHmaN2/eJZgKAAAAAHz8zBMAAAAA+AriCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAYIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAM+E09Hjx5VXFycUlNTjdavXbtWV111laKiojR9+vTKHQ4AAABAlecT8XT06FH16dPHOJwyMjKUkJCgAQMGaNOmTVq8eLHWrFlTuUMCAAAAqNICvD2AJPXv318DBw7U5s2bjdYvXrxY9erV08SJE2WxWDRp0iTNmzdPXbt2LXG9w+GQw+Fw37fb7RUyd2XKyT7q7REuK4UF+crNyfL2GKhCgoIj5efvE7+F+jx+P8OlkpeXp4yMDG+Pcdkp+pnxszt/0dHRCgwM9PYYuIR84k/+uXPnKi4uTmPGjDFav337dnXt2lUWi0WS1LFjRz355JOlrp86daomT55cIbNWtpCQEAVYrfrPtx97exQAqDABVqtCQkK8PQaucBkZGUpOTvb2GJetJUuWeHuEy87DDz+s+vXre3sMXEIWl8vl8vYQRSwWiw4cOKBGjRqVue6uu+7S9ddfr8cff1ySdOrUKdWrV08nTpwocX1JZ55iY2N14sQJhYeHV9j8FSUrK0unTp3y9hiXFafTqaysLG+PgSokMjJSVqvV22NcNkJCQhQZGentMXCF48wTLjXOPF0Z7Ha7IiIijNrAJ848na+AgADZbDb3/aCgIOXk5JS63mazeaz3dZGRkfwlAwCA8xQYGMhZAACVyic2jDhfNWrU8PiXpezsbKofAAAAQKW6LOOpQ4cO2rRpk/t+SkoK/9IEAAAAoFL5dDzZ7XY5nc5ijyckJGjjxo1atWqVnE6nXn75ZfXo0cMLEwIAAACoKnw6nuLj47V8+fJij0dFRWnGjBnq3bu3ateurb179+qZZ57xwoQAAAAAqgqf2m3vfB04cEB79uxR586dFRoaanzc+eyoAQAAAODKdcXvtlckLi5OcXFx3h4DAAAAQBXg05ftAQAAAICvIJ4AAAAAwADxBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPAAAAAGCAeAIAAAAAA8QTAAAAABggngAAAADAAPEEAAAAAAaIJwAAAAAwQDwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMBAgLcH8AaXyyVJstvtXp4EAAAAgDcVNUFRI5SlSsZTdna2JCk2NtbLkwAAAADwBdnZ2YqIiChzjcVlklhXmMLCQqWnpyssLEwWi8Xb4wBeYbfbFRsbq7S0NIWHh3t7HACAl/DnAao6l8ul7Oxs1atXT35+Zb+rqUqeefLz81NMTIy3xwB8Qnh4OH9YAgD48wBVWnlnnIqwYQQAAAAAGCCeAAAAAMAA8QRUUTabTc8++6xsNpu3RwEAeBF/HgDmquSGEQAAAABwvjjzBAAAAAAGiCcAAAAAMEA8AQAAAIAB4gkAAAAADBBPQBXwl7/8RSEhIcrKypIkpaamymKxKDU11atzAQAq15gxY3T33Xe77+fk5KhmzZr66quvvDcUcBkjnoAqIicnR/Pnz/f2GACAS2jcuHFavny5Dh48KElauHChmjZtqltvvdW7gwGXKeIJqCL8/f01e/Zs8ekEAFB1NGzYUHfddZdmzpwpl8ulv/3tb/rzn//s7bGAyxbxBFQRt956qzIyMvTZZ595PL5u3Tq1bdtW1atX18CBA92X9gEArgx//vOfNX/+fC1ZskSFhYXq27evJOnzzz9X69atFRkZqcTERDkcDvcxM2bMUL169RQWFqZ+/fopNzfXW+MDPoV4AqqI0NBQ3X///Zo1a5b7sbS0NPXu3VsPP/ywvvvuO508eVJDhw713pAAgAoXHx+v66+/Xg888IAmTJggPz8//fzzz7r99ts1ZswYbd26VVu2bNG0adMkSXv27NHjjz+uDz74QN9//71+/vlnLVy40MvfBeAbArw9AIBL55FHHlHLli21b98+SdKGDRt044036sEHH5QkvfHGG4qJidGRI0dUp04db44KAKhAI0aM0Nq1azVkyBBJ0ocffqi2bdsqMTFRkjRq1CjNnz9fzzzzjGw2myQpLy9PcXFx2rx5s9fmBnwN8QRUIU2aNFHPnj2VnJwsSVq/fr0aN27sfr5+/fqy2Wz65ZdfiCcAuIJEREQoMDDQHUa//vqrUlJSFBkZKUnKz89XaGioJCkuLk5vvfWWkpKS9PPPP6tnz56aOXOmoqOjvTU+4DO4bA+oYsaMGaOPP/5YknTLLbdo//797ufS09PlcDjUsGFDb40HALgEYmJi9Mc//lHbtm3Ttm3btH37dq1cuVLSmT8L2rdvr61btyo1NVVHjx7VlClTvDwx4BuIJ6CK6datm1q0aCFJuummm/T1119r7ty5OnDggEaOHKk77rhDtWvX9vKUAIDK1L9/f61fv14//fSTbDabXn/9dQ0bNkyStHPnTnXv3l0bN25Udna2pDNnpgAQT0CVNHr0aElSbGysli9fruTkZF177bUKDg7WO++84+XpAACVrUmTJlq0aJHGjRunpk2b6ocfftD7778vSerevbuGDx+ue+65R82bN5fL5dIzzzzj5YkB32Bx8aEvAAAAAFAuzjwBAAAAgAHiCQAAAAAMEE8AAAAAYIB4AgAAAAADxBMAAAAAGCCeAAAAAMAA8QQAwP/3ww8/aM+ePRf9OkeOHNGpU6cqYCIAgC/hc54AAD7D4XDo9OnT5a4LDw+Xn9///v0vLy9PFotFAQEBslgs5R5fUFCggoICBQYGejzeq1cvxcTEaO7cuZKktLQ0vfvuu/rqq6/0ySefFFtfmocffljr1q3Tjh07jNYDAC4PnHkCAPiM1157TdWrVy/3du7ZoRdeeEGBgYHy8/OTxWIp9xYQEKCHHnqo2Ne32WwKCQmRJO3bt08NGjTQwoULdfXVVys9PV316tVTVFSU+zZs2DD3sWdH38aNG3XXXXdJklwul06fPq3ffvvN49ii2+HDhyvjRwkAqAQB3h4AAIAiQUFBatiwoVJTU0t8fufOnWrdurWCgoI8Hh89erQSExNltVrl7+8vSTp8+LC6d++u6tWr69NPP1VoaKikM2edTp8+rWrVqrmPz8vLk5+fn/z9/RUcHCyHw6GaNWtKkv7xj3/ommuukXTmzNiLL76orl276qmnnlJubq77NWrUqKGAgAD5+fnJbrfrl19+0cyZM5WXlyeHw6GMjAxlZmbq559/VsOGDbVgwQI999xzqlu3boX9/AAAlYt4AgD4DD8/Px08eLDcS+/OvmRPOhMuNWrUcN9PT0/XwIEDdeTIEf3tb39To0aN5HA4ZLPZSny9p556Sq+++qr7/tSpU/Xzzz8XWxcaGqq6deuqadOmCg8Pl9PpdD9XdOZp8uTJWrJkiXbt2uVxrN1ulyT5+/srICBA33//vW6++eYyv08AgG/hsj0AgM8oKChQ/fr1deDAgRJvX3zxhXtdaVatWqVrr73WHT9+fn7au3evYmJi9MILL5S4kcPEiROVkZGhhIQEPfHEEzp8+LAaNWpUbN25UXfu/ezsbM2aNUtjx44tduy5wbd161bddNNNpX4fAADfQzwBAHxG0Zmc/Pz8Em9F0XT2GZ8imZmZGj58uHr06KHw8HAtW7bM/Zyfn5+uu+46Pf3002rSpImSk5M9XiMiIkJRUVGyWq0KCgpSnTp13Jf/nY9Jkybp6NGjevDBBz3eY1UUfUUcDod++OEH4gkALjPEEwDAZzidTh06dEjNmjUr8da7d2/3uiJHjhzRs88+q+bNm+udd97RuHHjtG3bNsXHx7vXNGvWTF988YVWrFihmjVr6pFHHlHbtm21ZcuWEufYvXt3mWe3SvL5558rOTlZfn5++ve//y2XyyWXy6WaNWsWe4/W999/L6vVqtatW5/X1wAAeBfxBADwuszMTGVlZWn06NHKzs4u9xYXF6fjx48rKytLP/zwg6ZMmaKbb75ZO3fu1LRp09w75p3rD3/4g1JSUjRlyhSlpqYqIMDzrb9Op1Pz58/X1VdfrZycHOP5169fr3vvvVdPPfWUx0YURc49i1WjRg35+flp69atxl8DAOB9bBgBAPC6Ll26FNtgwUS/fv30wQcfaO/evWratKkcDod7BzyHwyHpTBCdvSueJD399NMaOXKkatasqZycHCUnJ+vdd9/Vjh071LJlSy1evLjUACtJnTp11Lt3b02cOFGvvPKK+vfv7w6zoo0iztaiRQu99NJLGjJkiHbu3Cmr1Xre3zsA4NLjzBMAwOu+/vprZWdnKy8vTykpKXI6nXI6nfrqq68kyX2/6JaXl6ecnBzNmzdP0pnL8r777jtVq1bNfSva8GHgwIEej1erVk0HDx50b0UeGBiomTNnKjw8XPHx8erXr58GDBjgscHDmDFjlJeXV+r8zZo10wcffOA+w/TBBx8oKytLWVlZHrsAnm3EiBEKDAzUwoULL/bHBwC4RIgnAIDXhYeHKzQ0VEePHtW1116r2bNnKyAgwB0jqampSk1N1f79+/XTTz9p9+7dCgoK8jg7VPS+oi+++KLU3fqKYiswMNB9XEBAgNavX68NGzaoWbNmxWabO3eu3njjDe3fv9/4++nfv78iIyMVGRmpY8eOlbjGYrGoS5cu+uyzz4xfFwDgXVy2BwDwGYsXL5Yk3XbbbR6Pd+rUSS6XS4WFhSooKJDD4ZDdbvfYiKEotOrVq1fiNuOSVKtWLUnFtw0vaX1aWpok6fXXX9e7776rli1bup9LTk7Wv//9byUkJJT4dT744AP16dNHkhQVFVXs+RMnTiglJUXLli1T3759S3wNAIDv4cwTAMAnHDt2TK+++qqsVqv69evn8R6ozMxMHTt2TFlZWe7L+87dwa68D9Y9X4cPH5Z05gNzBw0a5PHc+vXr5XQ6i0VeaSwWi1wul/v+22+/ra5du6pDhw6aMmVKxQ0NAKhUnHkCAHhdXl6e7rvvPp0+fVo7duzQ/Pnz1b59ezVu3FjSmW3Ao6Oj3cGUm5sru92u48eP64477pCfn597a3GT7b/PDhnpzOdKuVwuHT9+3B1hHTt21JIlS3TPPfcUO37OnDkKDQ0tdgar6LUkKSsrS8nJyTp+/Lhq1Kjh8Z6p4cOH6/bbb1fTpk1NfjwAAB9BPAEAvG7QoEFavXq1/v3vf7t3ohs3bpzef/99ffXVV3rsscd07NgxZWdne+ycd9999+nOO++U9L/d9T7++OMS37skSV999ZVGjhzpXltk2bJluvvuu+Xn56fx48e7Hz83nAoKClRYWKjw8PASX9/lcrlfOyAgQC+//LIeeeQRtWzZUkeOHHGvCw0NJZwA4DJkcZ37z28AAFxidrtdu3fvVqdOnS74NRwOhw4fPqz69euf99bf+fn5eu+999S9e3fVq1ev1HXR0dFKTk7Wvffea/S6eXl57s0pCgoKlJaWppiYmGKfLwUAuDwQTwAAAABggA0jAAAAAMAA8QQAAAAABognAAAAADBAPAEAAACAAeIJAAAAAAwQTwAAAABggHgCAAAAAAPEEwAAAAAY+H8kQ530NXGHhwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))\n",
    "sns.boxplot(data=data, x=\"是否抑郁\", y=\"学习压力\", palette=\"coolwarm\")\n",
    "plt.title(\"学习压力与抑郁的关系\", fontsize=14)\n",
    "plt.xlabel(\"是否抑郁\", fontsize=12)\n",
    "plt.ylabel(\"学习压力\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\30226\\AppData\\Local\\Temp\\ipykernel_7676\\1516997864.py:2: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  sns.violinplot(data=data, x=\"是否抑郁\", y=\"年龄\", palette=\"muted\")\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "sns.violinplot(data=data, x=\"是否抑郁\", y=\"年龄\", palette=\"muted\")\n",
    "plt.title(\"年龄分布与抑郁情况的关系\", fontsize=14)\n",
    "plt.xlabel(\"是否抑郁\", fontsize=12)\n",
    "plt.ylabel(\"年龄\", fontsize=12)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "性别           0\n",
      "年龄           0\n",
      "学习压力         0\n",
      "学习满意度        0\n",
      "睡眠时间         0\n",
      "饮食习惯         0\n",
      "是否有过自杀的念头    0\n",
      "学习时间         0\n",
      "经济压力         0\n",
      "精神疾病家族史      0\n",
      "是否抑郁         0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 检查缺失值\n",
    "print(data.isnull().sum())\n",
    "\n",
    "# 选择填充或删除\n",
    "# data.dropna(inplace=True)  # 删除含有缺失值的行\n",
    "# data.fillna({'学习压力': data['学习压力'].mean(), '经济压力': data['经济压力'].mean()}, inplace=True)  # 填充缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将学习时间限制在0到12小时之间\n",
    "data = data[(data['学习时间'] >= 0) & (data['学习时间'] <= 12)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义睡眠时间的映射关系\n",
    "time_mapping = {\n",
    "    'more than 8 hours': 8,\n",
    "    '7-8 hours': 7,\n",
    "    '5-6 hours': 5,\n",
    "    'less than 5 hours': 4\n",
    "}\n",
    "\n",
    "# 应用映射关系\n",
    "data['睡眠时间'] = data['睡眠时间'].map(time_mapping)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将性别转换为数值型数据\n",
    "data['性别'] = data['性别'].map({'男': 1, '女': 0})\n",
    "\n",
    "# 将饮食习惯转换为数值型数据\n",
    "data['饮食习惯'] = data['饮食习惯'].map({'Healthy': 3, 'Moderate': 2, 'Unhealthy': 1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "#保存清洗后的数据\n",
    "data.to_csv('students_cleaned.csv', index=False, encoding='utf-8-sig')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count    502.000000\n",
      "mean      26.241036\n",
      "std        4.896501\n",
      "min       18.000000\n",
      "25%       22.000000\n",
      "50%       26.500000\n",
      "75%       30.000000\n",
      "max       34.000000\n",
      "Name: 年龄, dtype: float64\n",
      "count    502.000000\n",
      "mean       6.404382\n",
      "std        3.742434\n",
      "min        0.000000\n",
      "25%        3.000000\n",
      "50%        7.000000\n",
      "75%       10.000000\n",
      "max       12.000000\n",
      "Name: 学习时间, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# 数值数据统计描述\n",
    "print(data['年龄'].describe())\n",
    "print(data['学习时间'].describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将 '是否抑郁' 列转换为数值类型，例如将 'Yes' 转换为 1，'No' 转换为 0\n",
    "data['是否抑郁'] = data['是否抑郁'].map({'Yes': 1, 'No': 0})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          学习压力      学习时间      经济压力      是否抑郁\n",
      "学习压力  1.000000  0.053024  0.003168  0.476259\n",
      "学习时间  0.053024  1.000000  0.015554  0.200441\n",
      "经济压力  0.003168  0.015554  1.000000  0.296846\n",
      "是否抑郁  0.476259  0.200441  0.296846  1.000000\n"
     ]
    }
   ],
   "source": [
    "# 相关性分析\n",
    "correlation_matrix = data[['学习压力', '学习时间', '经济压力', '是否抑郁']].corr()\n",
    "print(correlation_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic 0:\n",
      "10 12 11\n",
      "Topic 1:\n",
      "11 10 12\n",
      "Topic 2:\n",
      "12 10 11\n"
     ]
    }
   ],
   "source": [
    "# 主题分析（以学习相关文本为例）\n",
    "from sklearn.decomposition import LatentDirichletAllocation\n",
    "lda_model = LatentDirichletAllocation(n_components=3, random_state=42)\n",
    "lda_matrix = lda_model.fit_transform(tfidf_matrix)\n",
    "for topic_idx, topic in enumerate(lda_model.components_):\n",
    "    print(f\"Topic {topic_idx}:\")\n",
    "    print(\" \".join([feature_names[i] for i in topic.argsort()[:-5 - 1:-1]]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 可视化分析结果\n",
    "# 绘制学习压力与是否抑郁的柱状图\n",
    "sns.countplot(x='学习压力', hue='是否抑郁', data=data)\n",
    "plt.title('学习压力与抑郁情况')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制年龄与是否抑郁的散点图\n",
    "sns.scatterplot(x='年龄', y='是否抑郁', data=data)\n",
    "plt.title('年龄与抑郁情况')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 绘制学习压力等级与抑郁比例柱状图\n",
    "pressure_depression = data.groupby('学习压力')['是否抑郁'].mean().reset_index()\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.bar(pressure_depression['学习压力'], pressure_depression['是否抑郁'])\n",
    "plt.xlabel('学习压力')\n",
    "plt.ylabel('抑郁比例')\n",
    "plt.title('学习压力等级与抑郁比例')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 绘制年龄与抑郁比例折线图\n",
    "age_depression = data.groupby('年龄')['是否抑郁'].mean().reset_index()\n",
    "\n",
    "plt.plot(age_depression['年龄'], age_depression['是否抑郁'])\n",
    "plt.xlabel('年龄')\n",
    "plt.ylabel('抑郁比例')\n",
    "plt.title('年龄与抑郁比例')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# 绘制睡眠时间分类与抑郁比例柱状图\n",
    "sleep_depression = data.groupby('睡眠时间')['是否抑郁'].mean().reset_index()\n",
    "\n",
    "sns.barplot(data=sleep_depression, x='睡眠时间', y='是否抑郁')\n",
    "plt.title('睡眠时间与抑郁比例')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
